Journal: Cancer Medicine

Article Title: Membranous and nuclear staining of CLDN18 in HPV ‐independent and HPV ‐associated endocervical adenocarcinomas

doi: 10.1002/cam4.5029

Figure Lengend Snippet: Expression of immunohistochemical markers in different ECA subtypes. Each graph shows the positive or aberrant expression rates of CDX2, PAX8, p16, p53, CEA, CLDN18 (M), and CLDN18 (N). (A) Gastric‐type ECA ( n = 8). (B) Intestinal‐type ECA ( n = 9). (C) iSMILE‐type ECA ( n = 8). (D) Usual‐type ECA ( n = 33). ECA, endocervical adenocarcinoma.

Article Snippet: After dewaxing and antigen retrieval, endogenous peroxidase activity was blocked with 0.3% hydrogen peroxide for 10 min. After blocking with goat serum, the sections were incubated for 30 min at 37°C with rabbit anti‐CLDN18 (1:500 dilution, clone ab203563; Abcam), rabbit anti‐CDX2 (1:50 dilution, clone A20222; ABclonal Technology Co), rabbit anti‐PAX8 (1:100 dilution, clone bs‐1201R; BIOSS ANTIBODIES), mouse anti‐CEA (1:300 dilution, clone 12‐140‐10; ZSGB‐BIO), mouse anti‐p53 (1:300 dilution, clone DO‐7; ZSGB‐BIO), and mouse anti‐P16 (1:100 dilution; clone MX007, MXB).

Techniques: Expressing, Immunohistochemical staining

Journal: Cancer Medicine

Article Title: Membranous and nuclear staining of CLDN18 in HPV ‐independent and HPV ‐associated endocervical adenocarcinomas

doi: 10.1002/cam4.5029

Figure Lengend Snippet: Immunohistochemical expression profiles of CLDN18 (M), CDX2, and PAX8 in G‐ECA, I‐ECA, U‐ECA, ECA‐iSMILE, and SQCC. The tumor cells of the I‐ECA exhibited gastric differentiation characterized by CLDN18 (M)‐positivity. ECA‐iSMILE, invasive stratified mucin‐producing carcinoma; G‐ECA, gastric‐type ECA; I‐ECA, intestinal‐type ECA; SQCC, squamous cell carcinoma (bar = 500 μm); U‐ECA, usual‐type ECA.

Article Snippet: After dewaxing and antigen retrieval, endogenous peroxidase activity was blocked with 0.3% hydrogen peroxide for 10 min. After blocking with goat serum, the sections were incubated for 30 min at 37°C with rabbit anti‐CLDN18 (1:500 dilution, clone ab203563; Abcam), rabbit anti‐CDX2 (1:50 dilution, clone A20222; ABclonal Technology Co), rabbit anti‐PAX8 (1:100 dilution, clone bs‐1201R; BIOSS ANTIBODIES), mouse anti‐CEA (1:300 dilution, clone 12‐140‐10; ZSGB‐BIO), mouse anti‐p53 (1:300 dilution, clone DO‐7; ZSGB‐BIO), and mouse anti‐P16 (1:100 dilution; clone MX007, MXB).

Techniques: Immunohistochemical staining, Expressing

Journal: Briefings in Bioinformatics

Article Title: Network-guided identification of cancer-selective combinatorial therapies in ovarian cancer

doi: 10.1093/bib/bbab272

Figure Lengend Snippet: Profiling data available from the 4 HGSOC patient cell cultures ex vivo

Article Snippet: To detect the surviving cells of different subpopulations at the end of drug treatment, the cells were fixed with 4% paraformaldehyde and immunostained with polyclonal anti-PAX8 rabbit antibody (Peprotech) using automated liquid handling.

Techniques: Imaging, Cytometry, Viability Assay, Sequencing, Ex Vivo

Journal: Briefings in Bioinformatics

Article Title: Network-guided identification of cancer-selective combinatorial therapies in ovarian cancer

doi: 10.1093/bib/bbab272

Figure Lengend Snippet: Construction and validation of the multi-patient and patient-specific predictive models. For a given sample, each drug was associated with a feature vector corresponding both to its drug-target profile and to the gene expression profile (decomposed from bulk RNA-seq) and point mutation detections (extracted from WGS) of the particular sample (left). In each iteration of 10-fold CV, 90% of the drug-sample feature matrix were used for training and the remaining 10% was used for testing of the monotherapy prediction accuracy, either using the PAX8+ and PAX8- samples from a single patient case (right, Patient-specific model), or all the patient samples (multi-patient model).

Article Snippet: To detect the surviving cells of different subpopulations at the end of drug treatment, the cells were fixed with 4% paraformaldehyde and immunostained with polyclonal anti-PAX8 rabbit antibody (Peprotech) using automated liquid handling.

Techniques: Biomarker Discovery, Plasmid Preparation, Gene Expression, RNA Sequencing, Mutagenesis

Journal: Briefings in Bioinformatics

Article Title: Network-guided identification of cancer-selective combinatorial therapies in ovarian cancer

doi: 10.1093/bib/bbab272

Figure Lengend Snippet: Coverage of PAX8 marker gene detection using deconvoluted RNA-seq data

Article Snippet: To detect the surviving cells of different subpopulations at the end of drug treatment, the cells were fixed with 4% paraformaldehyde and immunostained with polyclonal anti-PAX8 rabbit antibody (Peprotech) using automated liquid handling.

Techniques: Marker

Journal: Briefings in Bioinformatics

Article Title: Network-guided identification of cancer-selective combinatorial therapies in ovarian cancer

doi: 10.1093/bib/bbab272

Figure Lengend Snippet: Overlap of marker genes detected in EOC0939_pAsc scRNA-seq data versus fresh tumor samples. ( A ) PAX8+ markers, ( B ) PAX8- markers. The marker genes were detected from the scRNA-seq data with Wilcoxon test, using adjusted P < 0.01 and log fold-change > 1 cutoffs. Fresh tumor, scRNA-seq from fresh dissociated tissue; before culture, scRNA-seq from cryopreserved dissociated tissue; after culture, scRNA-seq from cultured cryopreserved dissociated tissue after 1 week in culture.

Article Snippet: To detect the surviving cells of different subpopulations at the end of drug treatment, the cells were fixed with 4% paraformaldehyde and immunostained with polyclonal anti-PAX8 rabbit antibody (Peprotech) using automated liquid handling.

Techniques: Marker, Cell Culture